909 resultados para GPU acceleration
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The behavior of average velocities on a dissipative version of the classical bouncer model is described using scaling arguments. The description of the model is made by use of a two-dimensional nonlinear area contracting map. Our results reveal that the model experiences a transition from limited to unlimited energy growth as the dissipation vanishes. (c) 2007 Elsevier B.V. All rights reserved.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The time and the distance traveled during the acceleration and the velocity retaking are parameters used for the comparison and the project of vehicles. In this paper equations for the calculation of those parameters are presented. Several criteria are presented for the shift gears. It is also verified the occurrence or not of total slip during the acceleration of the vehicle. The theoretical models were implemented in a developed computational system. Such system was applied in a Mercedes-Benz do Brazil sample vehicle, in order to facilitate comparisons between the simulate values and the experimental road tests. Copyright © 1997 Society of Automotive Engineers, Inc.
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We investigate the decay of accelerated protons and neutrons. Calculations are carried out in the inertial and coaccelerated frames. Particle interpretation of these processes are quite different in each frame but the decay rates are verified to agree in both cases. For the sake of simplicity our calculations are performed in a two-dimensional spacetime since our conclusions are not conceptually affected by this. ©1999 The American Physical Society.
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Includes bibliography
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In this article we explore the NVIDIA graphical processing units (GPU) computational power in cryptography using CUDA (Compute Unified Device Architecture) technology. CUDA makes the general purpose computing easy using the parallel processing presents in GPUs. To do this, the NVIDIA GPUs architectures and CUDA are presented, besides cryptography concepts. Furthermore, we do the comparison between the versions executed in CPU with the parallel version of the cryptography algorithms Advanced Encryption Standard (AES) and Message-digest Algorithm 5 (MD5) wrote in CUDA. © 2011 AISTI.
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Incluye Bibliografía
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Incluye Bibliografía